Generative Artificial Intelligence and its impact on the educational quality of students: Systematic Review

Solano Hilario C.; Belinda Ccope Jaucha K.; La Rosa de Benavides L.M.A.; Paul Medina Perez G. · Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology (2024) · DOI: 10.18687/laccei2024.1.1.1481

Resumen

Generative artificial intelligence (Gen AI) is rapidly gaining traction in the educational landscape. Gen AI, a subtype of AI, interacts with users in a conversational manner to generate text, audio, or video responses, providing students with a diverse range of structured answers and expanding their search horizons. However, as a relatively new technology, the impact of Gen AI on students has not been extensively evaluated in recent years. Against this backdrop, this study aims to identify how GenAI tools enhance student learning compared to traditional tools. To achieve this objective, a systematic literature review was conducted, incorporating bibliometric analysis to address PICO sub-questions. Following the PRISMA guidelines, a search strategy and inclusion/exclusion criteria were developed, and the study selection process was documented, resulting in the selection of 20 open-access research articles from the Scopus database. The findings indicate an equal preference for Gen AI and traditional tools. Additionally, personalization, feedback, and feedforward are identified as key factors in technological development for improving student learning. This growing interest in AI and its connection to education across various academic disciplines highlights the need for further research and the importance of recognizing this technology's potential to enhance education. Teacher support is crucial for rapid student adoption of these tools.

Instituciones: Universidad Tecnológica del Perú